Summary Tumor sequencing data have revealed significant differences in mutation frequencies between racial and ethnic groups. Some of these differences can be attributed to environmental exposure, such as smoking frequency, but disparities persist even after adjustment for known factors. Well-described examples include TP53 mutations that are seen at elevated rates in breast cancers in African-Americans compared to Asian and non-Hispanic White women and KRAS mutations that are observed in higher rates in colorectal cancers from African-Americans relative to other racial groups. As cancer aggressiveness and survival can depend on what pathways are perturbed in a tumor, the frequency at which a cancer driver mutation occurs in a population should influence some of the observed racial disparities in outcomes. Emerging data from our lab and others suggest that germline genetic variants impact somatic events in tumors. We identified associations between AURKA variants and TP53 in head and neck squamous cell carcinomas from The Cancer Genome Atlas. We found that individuals with at least one AURKA allele previously associated with cancer risk were more likely to have gain-of-function TP53 mutations relative to individuals homozygous for the non-risk associated allele. These and other studies suggest an association between germline Genetic variants and somatic Mutations (GxM) in tumor development. This study will search for novel Genetic variants associated with TP53, PIK3CA, and KRAS Mutations in order to explain racial differences in tumor biology. In this study, we will test the innovative hypothesis that germline genetic variants that differ in frequency between racial groups drive the observed racial differences in frequency of somatic mutations. Our goals are to understand the association between somatic mutations, germline genetic variants and tumorigenesis in racial disparities, and to determine the biological impact of GxM associations on cancer phenotypes using in vitro models. Using existing genotype and mutation data, these goals will be accomplished in two aims: 1. To identify and characterize GxM associations for TP53 and PIK3CA mutations in breast cancer in order to understand how germline variants drive racial differences in somatic mutation frequency. Variants found in GxM association studies from 3700 individuals with breast cancer will be evaluated in 4000 additional breast cancer cases from multiple racial and ethnic groups. Top GxM interactions will be assessed functionally using CRISPR/Cas9 to create knock-in and knock-out mutations and alleles. 2. To identify and characterize GxM associations for KRAS mutations in colorectal cancer (CRC) using a similar approach in Aim 1. These studies will apply a novel concept to discover new biological drivers for racial disparities in cancer outcomes, as measured by mutation frequencies. Results from this study have the potential to inform mechanistic studies which, in turn, will lead to new therapeutic strategies for cancers showing racial differences in mutation frequency and outcome.